Skip to main content
Glama
sanjeev7e

notebooklm-mcp-rpc

by sanjeev7e

Generate a mind map

generate_mind_map

Generates a mind map from a NotebookLM notebook, optionally restricted to specific source IDs or with a context label.

Instructions

Generate a mind map. Returns the JSON content directly (mind maps are stored as notes).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebookYesNotebook UUID.
sourceIdsNoRestrict generation to these source IDs.
contextLabelNo
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds value beyond annotations by stating that the tool returns JSON content directly and that mind maps are stored as notes. However, it does not disclose side effects or required permissions. Annotations already indicate it is a write operation (readOnlyHint=false) and open-world, so the added context is moderate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise—two sentences that front-load the main action. No unnecessary words, ideal for quick parsing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 parameters and no output schema, the description provides minimal context: return format and storage. It does not explain parameter semantics or output structure, leaving gaps that an agent would need to infer.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description does not elaborate on any of the three parameters (notebook, sourceIds, contextLabel). With schema coverage at 67%, the description fails to compensate for the missing parameter documentation or add meaning beyond the basic schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a mind map and returns JSON content, with a note that mind maps are stored as notes. This is a specific verb-resource combination, but it does not explicitly distinguish from sibling tools like generate_flashcards or generate_infographic.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions provided. The agent receives no context for appropriate invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sanjeev7e/notebooklm-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server